We recently sat down with the head of innovation of one of the world’s largest banks discussing his bank’s approach to big data. Numbers drive a bank.

Reviewing their big data strategy he symbolically points in the direction of their data center to say that they have “landfills of unused unstructured data.” They consist, he explained, of research, market reports, client inquiries, articles, comments both from internal and external sources. And they are growing fast.

The missing link is context

Similar case at another financial institution: A search on their internal database for ‘inflation’ returns more than 250’000 results. Too many results to be useful.

“We know this information would be extremely valuable for analysis,” says the head of the market analyst team. He explains what his analysts are after: A solution, which maps their inflation research inflation data. The result provides context to the data. To quote Derrek Harris of GigaOm: “Big Data needs context in order to be really useful; it’s context that turns disparate data points into a story.”

What is context?

Each of us immediately has a picture in our minds when hearing the word “Caterpillar”. However, without context, Caterpillar is a band, 2 companies, an insect and more than 120m results. Which of the multiple meanings of Caterpillar was the one you had in mind? Too many results to get to the relevant information quickly.

The proper definition of ‘context’ is a bit clumsy: “The circumstances that form the setting for an event, statement, or idea, and in terms of which it can be fully understood and assessed”, yet express well how to solve the ‘Caterpillar’ case. Add context to the initial query and you can filter down to the relevant quickly.

Others tell you ‘what’ – Squirro tells you ‘why’

This is exactly what Squirro does. Squirro reads out signals to construct a concept of the context you are in, before you actually retrieve information. This ‘profile’ – we call it digital fingerprint – is used to deliver unstructured data simply and in real time to the user in context of their own personal interests and priorities, learning and refining that precision as user interactions increase.

A great way to see the power of the concept is the integration of Squirro into Qlikview, a Business Intelligence solution. By combining the structured and the unstructured worlds, each insight uncovered in QlikView’s business discovery is used by Squirro to provide the ‘why’ behind the data.

Context Intelligence is vital

Context Intelligence solutions can crack the information retrieval problems outlined above, by streaming that unstructured data to the user in the right place at the right time. And in the process allow for better, more effective decision-making. Gartner in a research note back in 2010 identified context-aware computing as an emerging, game-changing opportunity for enterprises.